购买nlogit软件 保证正版
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关 键 词：购买nlogit软件
行 业：IT 软件 开发软件
发布时间：2021-03-14
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Nonlinear Least Squares Regression
Estimators
Nonlinear instrumental variables
Efficient GMM
Weighted nonlinear least squares
Model specification
Recursive function definition
Analytic or numeric derivatives
All algebraic operators and any level of parentheses
Matrix bilinear and quadratic forms
Mathematical functions (exp, sin, phi, gma, etc.)
Univariate and bivariate normal integrals
Hermite and Laguerre quadrature
Simulation estimation
Fixed parameters
Several algorithms
Statistics & Graphics
Descriptive statistics and graphical analysis tools include:
Descriptive statistics for cross sections and panels
Tables of means and quantiles
Time series
Spectral density
Graphics tools
Kernel density
Discriminant analysis
Contour plots
Probit and logit models
Bivariate probit models
Multivariate probit model
Partial observability
Sample selection
Multinomial (Logit) Choice Models
Random effects and random ultility models
Random regret
Latent class models
Ordered Choice Models
Bivariate ordered choice models
Sample selection models
Generalized ordered probit and logit models
Specifications for hierarchical models
Zero inflated ordered choice
Count Data Models
Specifications for censoring, truncation, and underreporting
Zero inflation and negative binomial (NB1, NB2, NBP, NBX)
Generalized Poisson
Gamma model
Quantile Poisson regression
Panel Data Models
Fixed effects for all models
Random effects for all models, quadrature and simulation estimators
Random parameters models
Latent class specifications
Tools
Specification analysis
Heteroscedasticity
Robust inference tools
Lagrange multiplier, likelihood and Wald tests
Model simulator for binary choice models
Matching and propensity score analysis
Average partial effects
Partial effects for interactions
Model simulation and prediction
Statistics
Numerous fit measures
Test statistics for specifications
Partial effects for all models
Interaction terms in model specification
Non- and Semiparametric Estimators
Least absolute deviations linear regression
Quantile regression, linear or count
Maximum score for binary choice
and Spady estimator for binary choice
Nonparametric, kernel density regression
LOWESS regression
Stratified Data
Cluster corrections
Stratification and clustering
Finite population weights
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